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Abstract:

Producers have adopted marketing strategies such as topping to help cut economic
losses at the processing plant. Even though producers are implementing these strategies, they are still missing target weights and receiving substantial discounts. To assess
this situation, we must first determine the accuracy of sampling methods producers use
to estimate the mean weight of the population. The standard sampling procedure that
has been adapted by many producers is to weigh a subsample of pigs in multiple pens
(i.e., 5 pigs from 6 pens). Using a computer program developed in R (R Foundation for
Statistical Computing, Vienna, Austria), we were able to generate 10,000 sample means
for different sampling procedures on 3 different datasets. Using this program we evalu-
ated taking: (1) a completely random sample of 10 to 200 pigs from the barn, (2) an
increasing number of pigs per pen from 1 to 15 or the entire pen, and (3) increasing the
number of pens until all pens had been sampled in the 3 separate datasets. This allowed
us to provide tables for producers to decide on the sampling method and size necessary
to achieve an acceptable estimation of pig weight in the barn. The analysis indicated that
the number of pigs can be decreased by increasing the number of pens; however, the
confidence interval (range in which 95% of weight estimates would fall) was still as high
as 23 lb (242 to 265 lb) when only 30 pigs were sampled. Increasing the number of pens
reduced the range between the upper and lower confidence interval, but not enough to
make increasing pen sample size a practical means of estimating mean pig weight of the
barn. Other methods of analysis must be designed to improve the accuracy of estimating pig mean weight in a facility other than random sampling of pigs within the barn.